The Resource Stochastic models with applications to genetics, cancers, AIDS, and other biomedical systems, by Wai-Yuan Tan, (electronic resource/)

Stochastic models with applications to genetics, cancers, AIDS, and other biomedical systems, by Wai-Yuan Tan, (electronic resource/)

Label
Stochastic models with applications to genetics, cancers, AIDS, and other biomedical systems
Title
Stochastic models with applications to genetics, cancers, AIDS, and other biomedical systems
Statement of responsibility
by Wai-Yuan Tan
Creator
Subject
Genre
Language
eng
Cataloging source
N$T
Dewey number
610.1/5195
Index
index present
LC call number
R853.M3
LC item number
T36 2015eb
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Series on concrete and applicable mathematics
Series volume
volume 19
Label
Stochastic models with applications to genetics, cancers, AIDS, and other biomedical systems, by Wai-Yuan Tan, (electronic resource/)
Link
http://library.quincycollege.edu:2048/login?url=http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=1091548
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface; 1 Introduction; 1.1. Some Basic Concepts of Stochastic Processes and Examples; 1.2. Markovian and Non-Markovian Processes, Markov Chains and Examples; 1.3. Diffusion Processes and Examples; 1.4. State Space Models and Hidden Markov Models; 1.5. The Scope of the Book; 1.6. Complements and Exercises; References; 2 Discrete Time Markov Chain Models in Genetics and Biomedical Systems; 2.1. Examples fromGenetics and AIDS; 2.2. The Transition Probabilities and Computation; 2.3. The Structure and Decomposition of Markov Chains
  • 2.4. Classification of States and the Dynamic Behavior of Markov Chains2.5. The Absorption Probabilities of Transient States; 2.5.1. The case when CT is finite; 2.5.2. The case when CT is infinite; 2.6. The Moments of First Absorption Times; 2.6.1. The case when CT is finite; 2.7. Some Illustrative Examples; 2.8. Finite Markov Chains; 2.8.1. The canonical form of transition matrix; 2.8.2. Absorption probabilities of transient states in finite Markov chains; 2.9. Stochastic Difference Equation for Markov Chains With Discrete Time; 2.9.1. Stochastic difference equations for finite Markov chains
  • 2.9.2. Markov chains in the HIV epidemic in homosexual or IV drug user populations2.10.Complements and Exercises; 2.11. Appendix; 2.11.1. The Hardy-Weinberg law in population genetics; 2.11.1.1. The Hardy-Weinberg law for a single locus in diploid populations; 2.11.1.2. The Hardy-Weinberg law for linked loci in diploid populations; 2.11.2. The inbreeding mating systems; 2.11.3. Some mathematical methods for computing An, the nth power of a square matrix A; References; 3 Stationary Distributions and MCMC in Discrete Time Markov Chains; 3.1. Introduction
  • 3.2. The Ergodic States and Some Limiting Theorems3.3. Stationary Distributions and Some Examples; 3.4. Applications of Stationary Distributions and Some MCMC Methods; 3.4.1. The Gibbs sampling method; 3.4.2. The weighted bootstrap method for generating random samples; 3.4.3. The Metropolis-Hastings algorithm; 3.5. Some Illustrative Examples; 3.6. Estimation of Linkage Fraction by Gibbs Sampling Method; 3.7. Complements and Exercises; 3.8. Appendix: A Lemma for Finite Markov Chains; References; 4 Continuous-Time Markov Chain Models in Genetics, Cancers and AIDS; 4.1. Introduction
  • 4.2. The Infinitesimal Generators and an Embedded Markov Chain4.3. The Transition Probabilities and Kolmogorov Equations; 4.4. Kolmogorov Equations for Finite Markov Chains with Continuous Time; 4.5. Complements and Exercises; References; 5 Absorption Probabilities and Stationary Distributions in Continuous-Time Markov Chain Models; 5.1. Absorption Probabilities and Moments of First Absorption Times of Transient States; 5.1.1. The case when CT is finite; 5.2. The Stationary Distributions and Examples; 5.3. Finite Markov Chains and the HIV Incubation Distribution
Control code
ocn928387326
Dimensions
unknown
Edition
2nd edition.
Extent
1 online resource (access may be restricted)
File format
unknown
Form of item
online
Governing access note
Access restricted to subscribing institution
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
eBooks on EBSCOhost
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
Label
Stochastic models with applications to genetics, cancers, AIDS, and other biomedical systems, by Wai-Yuan Tan, (electronic resource/)
Link
http://library.quincycollege.edu:2048/login?url=http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=1091548
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface; 1 Introduction; 1.1. Some Basic Concepts of Stochastic Processes and Examples; 1.2. Markovian and Non-Markovian Processes, Markov Chains and Examples; 1.3. Diffusion Processes and Examples; 1.4. State Space Models and Hidden Markov Models; 1.5. The Scope of the Book; 1.6. Complements and Exercises; References; 2 Discrete Time Markov Chain Models in Genetics and Biomedical Systems; 2.1. Examples fromGenetics and AIDS; 2.2. The Transition Probabilities and Computation; 2.3. The Structure and Decomposition of Markov Chains
  • 2.4. Classification of States and the Dynamic Behavior of Markov Chains2.5. The Absorption Probabilities of Transient States; 2.5.1. The case when CT is finite; 2.5.2. The case when CT is infinite; 2.6. The Moments of First Absorption Times; 2.6.1. The case when CT is finite; 2.7. Some Illustrative Examples; 2.8. Finite Markov Chains; 2.8.1. The canonical form of transition matrix; 2.8.2. Absorption probabilities of transient states in finite Markov chains; 2.9. Stochastic Difference Equation for Markov Chains With Discrete Time; 2.9.1. Stochastic difference equations for finite Markov chains
  • 2.9.2. Markov chains in the HIV epidemic in homosexual or IV drug user populations2.10.Complements and Exercises; 2.11. Appendix; 2.11.1. The Hardy-Weinberg law in population genetics; 2.11.1.1. The Hardy-Weinberg law for a single locus in diploid populations; 2.11.1.2. The Hardy-Weinberg law for linked loci in diploid populations; 2.11.2. The inbreeding mating systems; 2.11.3. Some mathematical methods for computing An, the nth power of a square matrix A; References; 3 Stationary Distributions and MCMC in Discrete Time Markov Chains; 3.1. Introduction
  • 3.2. The Ergodic States and Some Limiting Theorems3.3. Stationary Distributions and Some Examples; 3.4. Applications of Stationary Distributions and Some MCMC Methods; 3.4.1. The Gibbs sampling method; 3.4.2. The weighted bootstrap method for generating random samples; 3.4.3. The Metropolis-Hastings algorithm; 3.5. Some Illustrative Examples; 3.6. Estimation of Linkage Fraction by Gibbs Sampling Method; 3.7. Complements and Exercises; 3.8. Appendix: A Lemma for Finite Markov Chains; References; 4 Continuous-Time Markov Chain Models in Genetics, Cancers and AIDS; 4.1. Introduction
  • 4.2. The Infinitesimal Generators and an Embedded Markov Chain4.3. The Transition Probabilities and Kolmogorov Equations; 4.4. Kolmogorov Equations for Finite Markov Chains with Continuous Time; 4.5. Complements and Exercises; References; 5 Absorption Probabilities and Stationary Distributions in Continuous-Time Markov Chain Models; 5.1. Absorption Probabilities and Moments of First Absorption Times of Transient States; 5.1.1. The case when CT is finite; 5.2. The Stationary Distributions and Examples; 5.3. Finite Markov Chains and the HIV Incubation Distribution
Control code
ocn928387326
Dimensions
unknown
Edition
2nd edition.
Extent
1 online resource (access may be restricted)
File format
unknown
Form of item
online
Governing access note
Access restricted to subscribing institution
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
eBooks on EBSCOhost
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote

Library Locations

    • Nease Library - Eastern Nazarene College Borrow it
      23 East Elm Ave. , Quincy, MA, 02170, US
      42.271089 -71.012428
    • Quincy College Library Borrow it
      1250 Hancock St. 3rd Fl Rm#347, Quincy, MA, 02169, US
      42.2513682 -70.9962875
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